ArticleProceedings of the National Academy of Sciences of the United States of America2008
High-confidence prediction of global interactomes based on genome-wide coevolutionary networks.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 75 papers.
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Who cites it
75 citing papers in PubMed, 211 citations in OpenAlex.
- EvoWeaver: large-scale prediction of gene functional associations from coevolutionary signals.Nature communications · 2025Article
- Subspecies phylogeny in the human gut revealed by co-evolutionary constraints across the bacterial kingdom.Cell systems · 2025Article
- Pairing interacting protein sequences using masked language modeling.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Article
- An evolution-based framework for describing human gut bacteria.bioRxiv : the preprint server for biology · 2023Article
- Computational Network Inference for Bacterial Interactomics.mSystems · 2022Review
- Phylogenetic Permulations: A Statistically Rigorous Approach to Measure Confidence in Associations in a Phylogenetic Context.Molecular biology and evolution · 2021Article
- Selective Nutrient Transport in Bacteria: Multicomponent Transporter Systems Reign Supreme.Frontiers in molecular biosciences · 2021Review
- Article
- A multi-scale coevolutionary approach to predict interactions between protein domains.PLoS computational biology · 2019Article
- Landscape of the Plasmodium Interactome Reveals Both Conserved and Species-Specific Functionality.Cell reports · 2019Article
- Computational identification of protein-protein interactions in model plant proteomes.Scientific reports · 2019Article
- Building protein-protein interaction networks for Leishmania species through protein structural information.BMC bioinformatics · 2018Article
- Reconstructing phylogenetic tree using a protein-protein interaction technique.IET nanobiotechnology · 2017Article
- Diurnal Cycling Transcription Factors of Pineapple Revealed by Genome-Wide Annotation and Global Transcriptomic Analysis.Genome biology and evolution · 2017Article
- ChiPPI: a novel method for mapping chimeric protein-protein interactions uncovers selection principles of protein fusion events in cancer.Nucleic acids research · 2017Article
- Premammalian origin of the sperm-specific Slo3 channel.FEBS open bio · 2017Article
- Simultaneous identification of specifically interacting paralogs and interprotein contacts by direct coupling analysis.Proceedings of the National Academy of Sciences of the United States of America · 2016Article
- Great interactions: How binding incorrect partners can teach us about protein recognition and function.Proteins · 2016Article
- Predicting protein-protein interactions via multivariate mutual information of protein sequences.BMC bioinformatics · 2016Article
15 more citing papers are in PubMed but not listed here.
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Interacting or functionally related protein families tend to have similar phylogenetic trees. Based on this observation, techniques have been developed to predict interaction partners. The observed degree of similarity between the phylogenetic trees of two proteins is the result of many different factors besides the actual interaction or functional relationship between them. Such factors influence the performance of interaction predictions. One aspect that can influence this similarity is related to the fact that a given protein interacts with many others, and hence it must adapt to all of them. Accordingly, the interaction or coadaptation signal within its tree is a composite of the influence of all of the interactors. Here, we introduce a new estimator of coevolution to overcome this and other problems. Instead of relying on the individual value of tree similarity between two proteins, we use the whole network of similarities between all of the pairs of proteins within a genome to reassess the similarity of that pair, thereby taking into account its coevolutionary context. We show that this approach offers a substantial improvement in interaction prediction performance, providing a degree of accuracy/coverage comparable with, or in some cases better than, that of experimental techniques. Moreover, important information on the structure, function, and evolution of macromolecular complexes can be inferred with this methodology.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.